Computer Systems Engineer working on providing services from our Main office located at The Mille,1000 Great West Road, Brentford, England, TW8 9DW

While working on our projects on this project his duties will be as follows:

• Development in React JS and Redux
• Programming in HTML5, CSS pre-processors (CSS3, SASS, SCSS or LESS) ,
• and Bootstrap, Foundation or Materialize
• Programming JavaScript and ES5/ES6, Typescript, REST APIs
• Assign, Modifying and Publishing application access to the users.
• Develop software in TDD/BDD experience (Jest, Jasmine, Karma)
• Create client-side architecture and design patterns.
• Plan for cross-browser compatibility issues and client-side performance
• Plan for version control tools like Git, SVN or Mercurial
• Develop programs in React Native JS

To carry out above duties excellent skills in Windows Server, React JS and Redux HTML5, CSS pre-processors (CSS3, SASS, SCSS or LESS) , and Bootstrap, Foundation or Materialize JavaScript knowledge and programming experience with ES5/ES6 C language are required. Further the above duties can only be performed by an individual with a Bachelor's degree in the field of IT/MIS or its equivalent in a related field.

• Job Title: Data Scientist
• Location: Remote / Hybrid / On-site – London, England
• Company: Ramark Systems Ltd
• Job Type: Full-Time
• Experience Level: Mid-Level/ Senior-Level

Key Responsibilities

Data Exploration & Preprocessing

• Acquire data from internal and external sources via APIs, databases, data lakes, or streaming platforms.
• Perform exploratory data analysis (EDA) using statistical summaries, correlation matrices, and hypothesis testing.
• Cleanse, normalize, and transform data using tools such as Pandas, NumPy, and PySpark.
• Implement data validation, anomaly detection, and outlier handling processes.

Model Development & Machine Learning

• Build and validate supervised and unsupervised models including:
• Classification (e.g., logistic regression, random forests, XGBoost)
• Regression (e.g., linear models, gradient boosting, regularized models)
• Clustering (e.g., K-Means, DBSCAN, hierarchical)
• Dimensionality Reduction (e.g., PCA, t-SNE, UMAP)
• NLP (e.g., topic modeling, named entity recognition, sentiment analysis using spaCy, Hugging Face Transformers)
• Evaluate model performance using metrics such as AUC-ROC, F1-score, MAE/MSE, and confusion matrices.
• Apply cross-validation, hyperparameter tuning (e.g., GridSearchCV, Optuna, Bayesian Optimization).

Production Deployment & MLOps

• Package models using tools like MLflow, ONNX, or joblib for deployment.
• Integrate models into production pipelines using Docker, FastAPI, or Flask.
• Implement version control, CI/CD, and automated retraining pipelines.
• Monitor model drift and trigger re-training workflows via Airflow, Kubeflow, or Azure ML Pipelines.

Data Infrastructure & Engineering

• Work with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, BigQuery).
• Optimize data workflows and pipeline performance in Apache Spark, Databricks, or AWS Glue.
• Design and maintain feature stores, data marts, and cloud-native data solutions.

Visualization & Communication

• Build dashboards using Tableau, Power BI, or Plotly Dash.
• Develop automated reporting systems and story-driven data narratives.
• Translate analytical outcomes into business recommendations for stakeholders across product, engineering, and operations teams.

Required Technical Skills

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow, Matplotlib/Seaborn).
• Solid experience with SQL, ETL pipelines, and data warehouse solutions (e.g., Snowflake, Redshift).
• Familiarity with Git, JIRA, and Agile project management tools.
• Hands-on experience with cloud platforms: AWS (S3, SageMaker, Lambda), Azure (Data Factory, ML Studio), or GCP (Vertex AI, BigQuery).

Preferred Qualifications

• MSc/PhD in Computer Science, Statistics, Data Science, or a quantitative discipline.
• Experience with time-series analysis, deep learning, or generative AI.
• Exposure to DevOps/MLOps workflows, Kubernetes, and Terraform for scalable deployments.
• Prior work on recommendation systems, fraud detection, or optimization algorithms.

What We Offer

• Competitive salary + equity options + performance-based bonuses.
• Continuous learning budget for certifications, conferences, and online courses.
• Access to high-impact data projects across fintech, healthtech, and SaaS domains.
• Flexible remote work and strong focus on work-life balance.
• A collaborative, technically sophisticated team culture.